Spatial Decision Support Systems

From Wikiversity
Jump to: navigation, search
SDSS = GIS + DSS

A spatial decision support system (SDSS) is an interactive, computer-based system designed to assist in decision making while solving a semi-structured spatial problem.[1] It is designed to assist the spatial planner with guidance in making land use decisions. A system which models decisions could be used to help identify the most effective decision path. An SDSS is sometimes referred to as a policy support system, and comprises a decision support system (DSS) and a geographic information system (GIS). This entails use of a database management system (DBMS), which holds and handles the geographical data; a library of potential models that can be used to forecast the possible outcomes of decisions; and an interface to aid the users interaction with the computer system and to assist in analysis of outcomes.

Process[edit]

An SDSS usually exists in the form of a computer model or collection of interlinked computer models, including a land use model. Although various techniques are available to simulate land use dynamics, two types are particularly suitable for SDSS. These are cellular automata (CA) based models[2] and Agent based models (ABM).[3]

An SDSS typically uses a variety of spatial and nonspatial information, like data on land use, transportation, water management, demographics, agriculture, climate, epidemiology, resource management or employment. By using two or more known points in history the models can be calibrated and then projections into the future can be made to analyze different spatial policy options. Using these techniques spatial planners can investigate the effects of different scenarios, and provide information to make informed decisions. To allow the user to easily adapt the system to deal with possible intervention possibilities an interface allows for simple modification to be made.

Learning Task[edit]

[4]Long-term mean precipitation by month - created by Greenmind1980
Countries by average annual precipitation
  • (Risk Map) Search the web for spatio-temporal animation for the spread of flu. Decribe the decision support such an animation could provide for a public health agency (see Robert-Koch-Institut Flu Maps[5]. Learn how to create an animation with risk maps generated for created for different weeks (see How-To: Create GIF-Animation with GIMP).
  • (Response Map) Look at vaccination as one type of response that could be a counter measure for risk-mitigation. What could a spatial decision support system do for a public health agency in terms of resource allocation, public warnings in certain areas?
  • (Sustainable Development Goals) Analyse the Sustainable Development Goals[6] and identify spatial pattern of risk and scenarios of spatial allocation of resources according to risk. Describe the purpose of a spatial decision support system for selected Sustainable Development Goals (SDG)!
  • (Information Systems in General) Analyse the general characteristics of Information Systems and derive requirements and constraints for Spatial Decision Support Systems!
  • Spatial Decision Support Layers: A Geographic Information System is organized in layers with specific information (e.g. temperature, precipitation,). A decision support layer transforms GIS layers in specific spatial decision support products, that can be processed with the rule base (e.g. Fuzzy Controller).

See also[edit]

References[edit]

  1. Sprague, R. H., and E. D. Carlson (1982) Building effective Decision Support Systems. Englewood Cliffs, N.J.:Prentice-Hall, Inc.
  2. White, R., and G. Engelen (2000) High-resolution integrated modeling of spatial dynamics of urban and regional systems. Computers, Environment, and Urban Systems 24: 383–400.
  3. Parker, D. C., Manson, S. M., Marco A. Janssen, Hoffmann, M., Deadman, P., June (2003) Multi-agent systems for the simulation of land-use and land-cover change: A review. Annals of the Association of American Geographers 93 (2): 314–337.
  4. Karger, Dirk Nikolaus; Conrad, Olaf; Böhner, Jürgen; Kawohl, Tobias; Kreft, Holger; Soria-Auza, Rodrigo W.; Zimmermann, Niklaus; Linder, H. Peter et al. (2016-07-01). "Climatologies at high resolution for the Earth land surface areas". arXiv:1607.00217 [physics.ao-ph]. 
  5. Flu Maps by Robert-Koch-Institut 2017 - https://influenza.rki.de/MapArchive.aspx
  6. Griggs, D., Stafford-Smith, M., Gaffney, O., Rockström, J., Öhman, M. C., Shyamsundar, P., ... & Noble, I. (2013). Policy: Sustainable development goals for people and planet. Nature, 495(7441), 305-307.

External links[edit]